Photoplethysmography (PPG) is a technique that has been used since the 1930s for assessing cardiovascular function [1]. Its use has become widespread in hospitals due to its relatively low cost and ease of use. In its simplest form, it consists of two primary components: a light source and a light detector. The light source illuminates the tissue with constant optical power, and the light detector detects the amount of light transmitted through the tissue. The light output fluctuates with each blood pulse resulting from a cardiac cycle, resulting in the extraction of a blood pulse waveform or BPW.
PPG devices rely on the properties of light-tissue interaction. Light that penetrates the surface of the skin interacts with the underlying tissues in two primary ways: scattering and absorption. When perfectly reflected and scattered by a molecule, a photon of light changes direction and possibly polarization, but retains its original energy level. Alternatively, a photon of light may be absorbed by certain types of molecules called “chromophores” (such as hemoglobin and melanin), resulting in a fewer number of photons being re-emitted. Chromophores are thus characterized by spectral absorption profiles called “extinction coefficients”. As an illustrative example, when the heart enters systole during a cardiac cycle, blood is pumped through the arterial system, causing a transient increase in blood volume at the traveling area of the pulse. This change in blood volume modifies the temporal illumination profile passing through the vasculature, resulting in a BPW that is displayed on PPG monitors.
The first known PPG imaging (PPGI) system was proposed in 2002 by M. Hulsbusch and V. Blazek [2] using a cooled near infrared CCD camera to assess wound healing. The authors used a wavelet transform to show noisy pulsatile components around an ulcer wound. They further demonstrated preliminary results using transmittance through a fingertip. However, their setup was expensive, did not produce real-time analysis, and produced noisy BPW signals.
In 2005, Wieringa et al. published a PPGI system and method for extracting blood pulse oxygen levels [3]. Their PPGI system was controlled and synchronized to an ECG and finger cuff using a footswitch and in-frame background light. They used a combination of a modified camera (since obsolete), and 300 LED ring light of wavelength 660 nm, 810 nm, and 940 nm. Regions of 10×10 pixels were averaged to reduce noise. Their low frame rates limited the real-time applicability. This experiment, like many others, was assessed in darkroom settings, void of ambient light. The “relative spectral power” map was calculated with a hardcoded heart rate, and limited to the hand/wrist region of a subject.
In 2007, Humphreys et al. published a PPGI system that extended on Wieringa's [4]. An 8×8 LED grid separate from the camera was used to illuminate the skin. Synchronization was done using electronic switches. Like Wieringa's system, a background light was used for synchronization. However, the results were restricted to forearm measurements of heart rate and blood oxygen metrics only.
Since these initial studies, there have been other PPGI systems proposed. However, most of these systems are restricted to measuring heart rate [15] over either the hand/wrist area [5] or the face [6] [7] [8], and many rely on limited methods for reducing noise, such as windowed averaging [9] [10]. Moreover, many are validated only in darkroom settings [11] [5] [7], which limit their applicability in real-world, clinical environments where darkroom settings may be difficult to establish.
More recently, Kamshilin et al. [12] used two identical green LEDs and a camera along with a synthetic BPW to construct a visualization of pixel-by-pixel perfusion and pulsing. However, once again, their findings were restricted to constrained environments of hand/wrist imaging, and the method required prerequisite knowledge of the heart rate, and could not detect heart rate automatically. What is needed is an improved system and method for spatial cardiovascular monitoring that overcomes at least some of the above described limitations in the prior art.